A modified grey wolf optimization algorithm for an intrusion detection system
Cyber-attacks and unauthorized application usage have increased due to the extensive use
of Internet services and applications over computer networks, posing a threat to the service's …
of Internet services and applications over computer networks, posing a threat to the service's …
COVID-19 diagnosis and classification using radiological imaging and deep learning techniques: a comparative study
In December 2019, the novel coronavirus disease 2019 (COVID-19) appeared. Being highly
contagious and with no effective treatment available, the only solution was to detect and …
contagious and with no effective treatment available, the only solution was to detect and …
Multi-objective optimal scheduling of automated construction equipment using non-dominated sorting genetic algorithm (NSGA-III)
Y Liu, K You, Y Jiang, Z Wu, Z Liu, G Peng… - Automation in …, 2022 - Elsevier
Unstructured and variable construction sites bring challenges that can be addressed with
the adoption of the flexible earthwork scheduling problem (FESP), which requires …
the adoption of the flexible earthwork scheduling problem (FESP), which requires …
On the interest of Artificial Intelligence approaches in solving the IoT coverage problem
S Mnasri, M Alghamdi - Ad Hoc Networks, 2024 - Elsevier
This survey deals with the 3D indoor deployment in IoT collection networks to identify the
right locations of the IoT connected objects and, subsequently, to manage the coverage …
right locations of the IoT connected objects and, subsequently, to manage the coverage …
Magnetic force classifier: a Novel Method for Big Data classification
There are a plethora of invented classifiers in Machine learning literature, however, there is
no optimal classifier in terms of accuracy and time taken to build the trained model …
no optimal classifier in terms of accuracy and time taken to build the trained model …
IoT networks 3D deployment using hybrid many-objective optimization algorithms
When resolving many-objective problems, multi-objective optimization algorithms encounter
several difficulties degrading their performances. These difficulties may concern the …
several difficulties degrading their performances. These difficulties may concern the …
Smart city urban planning using an evolutionary deep learning model
M Alghamdi - Soft Computing, 2024 - Springer
Following the evolution of big data collection, storage, and manipulation techniques, deep
learning has drawn the attention of numerous recent studies proposing solutions for smart …
learning has drawn the attention of numerous recent studies proposing solutions for smart …
Metaheuristic algorithms based on compromise programming for the multi-objective urban shipment problem
The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially
logistics. In this study, we introduced an adaptive method to a complex VRP. It combines …
logistics. In this study, we introduced an adaptive method to a complex VRP. It combines …
From a Pareto front to Pareto regions: A novel standpoint for multiobjective optimization
This work presents a novel approach for multiobjective optimization problems, extending the
concept of a Pareto front to a new idea of the Pareto region. This new concept provides all …
concept of a Pareto front to a new idea of the Pareto region. This new concept provides all …
Energy-efficient IoT routing based on a new optimizer
S Mnasri, M Alrashidi - Simulation Modelling Practice and Theory, 2022 - Elsevier
Several difficulties are generally encountered when solving many-objective problems (fitted
with three or more conflictual objectives) by applying multi-objective algorithms (resolving …
with three or more conflictual objectives) by applying multi-objective algorithms (resolving …